Senior Scientist

Location:

Company:

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About AbsorbX

AbsorbX is a carbon credit marketplace building trust and transparency in the voluntary carbon market. We work with early-stage and established project developers to bring high-quality, high-integrity carbon credits to market. Our mission is to help organizations and individuals take credible, measurable climate action.

project rating framework

Role Overview

Climate & Carbon Scientist

Key Responsibilities

• Develop and maintain the

  scientific framework

  for project evaluation (across nature-based and tech-based removal methods).
• Build and validate

  carbon accounting methodologies

  for project types such as biochar, enhanced rock weathering (ERW), afforestation, and soil carbon.
• Define

  durability, additionality, and leakage

  baselines and scoring mechanisms for AbsorbX’s internal rating system.
• Design

  risk assessment parameters

  including project execution, delivery risk, permanence risk, and social co-benefits.
• Review project documentation (PDDs, LCA reports, third-party verifications) to validate emission reduction claims.
• Collaborate with the data and product teams to translate complex scientific frameworks into clear, user-facing insights.
• Stay up to date with latest registry methodologies (Verra, Gold Standard, Puro Earth, Isometric, Frontier) and academic research.

Requirements

Education & Experience:

• Advanced degree (Master’s or PhD preferred) in Environmental Science, Climate Science, Earth Systems, Carbon Management, or related field.
• 3–8 years of experience in

  carbon project assessment

  ,

  LCA

  , or

  carbon accounting

  — ideally across multiple project types.
• Deep familiarity with

  voluntary carbon market registries

  and MRV frameworks.
• Experience working with

  carbon durability modeling

  ,

  soil/biomass carbon

  , or

  carbon removal technologies

  .

Skills:

• Strong grasp of GHG Protocols, IPCC Guidelines, and ISO 14064 standards.
• Ability to develop or adapt carbon quantification models.
• Analytical mindset — able to interpret scientific uncertainty, leakage, permanence, and co-benefit tradeoffs.
• Experience using data tools (Python/R/Excel) or LCA software (SimaPro, OpenLCA) a plus.
• Excellent written communication skills — able to summarize scientific findings clearly.